1. Field of the Invention
The present invention relates generally to determining energy-output device parameters and, more specifically, to determining energy-output device impedance.
2. State of the Art
A battery converts stored chemical energy to electrical energy, which may be conveyed as a voltage source. As with any non-ideal voltage source, the battery will have an internal impedance including a combination of resistance and reactance. The internal impedance produces power loss in a system by consuming power as a voltage drop across the source impedance. Ideally, a perfect battery would have no source impedance and deliver any power to the extent of its stored energy, but this is not physically reasonable. Thus, within physical limits, a reduction in source impedance will increase deliverable power.
As a battery ages the internal impedance generally tends to become larger. A brand new battery will have a Beginning Of Life (BOL) impedance much smaller than the End Of Life (EOL) impedance. Similarly, storage capacity of the battery will decrease from BOL to EOL. Therefore, observations of battery parameters such as internal impedance and storage capacity may be used to determine the overall State Of Health (SOH) of a battery. When the internal impedance becomes too large and the battery capacity can no longer reliably deliver energy at the specified power the battery has effectively reached EOL. Furthermore, the rate of change of a battery's internal impedance may be closely related to the state of health of the battery. This is especially true when considering rechargeable or secondary cells. While different secondary battery chemistries undoubtedly perform differently throughout their lives, increases in internal impedance over life at certain frequencies show promise as a uniform method to classify SOH in most chemistries.
Battery impedance also may vary with the relative charge of the battery and temperature. In other words, a battery at half of its rated capacity will have different impedance than a battery at its full rated capacity. Similarly, a battery at different temperatures will exhibit different internal impedance characteristics.
Battery fuel gauges, battery capacity monitors, and battery status monitors attempt to predict battery capacities and give the user an idea of remaining capacity. Conventionally, battery capacity is estimated by current integration, voltage monitoring, or combinations thereof.
Current integration, or coulomb counting as it is commonly called, monitors the battery's available stored charge by measuring the amount of charge that enters and exits the battery through normal cycling. The basis for this approach is, that if all charge and discharge currents are known, the amount of coulometric capacity will be known.
Voltage monitoring methods are based on the recognized relationship between the battery terminal voltage and the remaining capacity. All that is required is voltage measurement of the battery terminals to acquire a rough idea of the State Of Charge (SOC) of the battery.
Both of these methods have limits when applied to actual conditions. Current integration requires a rigorous amount of external current tracking to remain accurate. SOC determination obtained from measurement and integration of external current suffers from errors caused by internal self-discharge currents. If the battery is not used for several days, this self-discharge current dissipates the charge within the battery and can affect the current integration approximation for battery charge.
Voltage monitoring may show errors when measurements are taken with load on the battery. When a load is applied, the voltage drop due to the internal impedance of the battery distorts battery voltage. For many batteries, such as lithium-ion batteries, even after the load is removed, slow time constants and relaxation processes may continue to change the battery voltage for hours. Also, some battery chemistries (e.g., nickel metal-hydride) exhibit a strong voltaic hysteresis, which hinders the possibility of using voltage to track capacity.
Usually, these two methods are combined to operate together under varying conditions. For example, current integration may monitor the SOC while under discharging and charging currents. Whereas, while the battery is at rest voltage monitoring may be employed to monitor self-discharge.
SOC algorithms and measurement techniques are well known, but methods to predict battery life, or state of health (SOH), are less common. As mentioned earlier, SOH is also very dependent on cell impedance. If the cell impedance dependencies on SOC and temperature are known, or closely approximated, it is possible to employ modeling techniques to determine when a discharged voltage threshold will be reached at the currently observed load and temperature. Cell impedance analysis for SOH may be enhanced even more if the battery impedance estimation process were fast enough to eliminate the impedance dependencies on comparatively slow changes like SOC variations and temperature variations. Therefore, a way to monitor battery impedance in-situ at near real time would greatly enhance SOC and SOH predictions due to aging cells.
Conventionally, Electrochemical Impedance Spectroscopy (EIS) is a popular method for analyzing battery impedance. EIS generates a sine excitation waveform at a specific frequency that is applied to the battery. The voltage and current responses are monitored and analyzed to arrive at battery impedance for that particular frequency. Then, the frequency of the sine excitation signal is modified over a range of frequencies to arrive at a frequency spectrum of the battery impedance. This process provides stable, accurate measurements of battery impedance, but is most practical for laboratory conditions, not during in-situ operation. In other words, EIS may not work well when the battery is under changing loads as changes imposed upon the sine wave excitation may skew the results. Also, the methodology of the EIS system is inherently serial (i.e., a single frequency for each step), making its application time consuming (often several hours) and inappropriate for a near real-time analysis.
Therefore, to enhance monitoring of life and in-situ charge of a battery or other energy-output device under normal conditions, there is a need for a method and apparatus for determining energy-output device impedance across a frequency spectrum using near real-time measurement and analysis that may be employed during in-situ operation.